Unverified50% confidenceBenchmarkExact time
On Multimodal RewardBench 2, JEV-27B-VL averages 63.8 across four tasks, close to GPT-4.1 and Qwen3-VL-32B but behind GPT-5 and Gemini 3 Pro; its image editing score of 57.8 is a clear weak spot.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/17/2026
First Seen
Valid until: 1/15/2027
Sources
Related Entities
Related Claims
UnverifiedOfficial model card scores for Qwen3.8-27B: GPQA Diamond 89.2, LiveCodeBench v6 90.3, SWE-bench Pro 61.7, Terminal Bench 2.1 73.0; Artificial Analysis Intelligence Index score of 52, on par with GPT-5.6 Luna, and just one point below GLM-5.2 (753B) and DeepSeek V4 Pro (1.7T).74% similarUnverifiedd1-3B averages 74.1 across 11 image benchmarks, versus 73.9 for LFM2.5-VL-3B; on VL-RewardBench d1-3B scores 65.0, far ahead of LFM2.5-VL-3B's 50.9, but it lags on CV-Bench (82.1 vs 87.6), VisualWebBench (71.4 vs 78.3), and POPE (88.5 vs 90.1).73% similarUnverifiedDataBugBench testing covers five models: Claude 3.5 Sonnet, GPT-4o, Gemini 1.5 Pro, Qwen 2.5 Coder 32B, and Llama 3.3 70B.66% similarUnverifiedOn VL-RewardBench, JEV-27B-VL achieves an overall accuracy of 78.3%, 83.2% on hallucination items, 78.2% on reasoning items, and 58.0% on general questions.65% similarUnverifiedThe label-image accuracy gaps of GPT-4o, Qwen-VL Max, and LLaMA reach 9.5, 13.8, and 12.6 percentage points respectively.65% similar
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